Documentation links below provide documentation for Neptune Database and Neptune Analytics:
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Neptune Database Learn more about Neptune Database - a fully managed graph database that you can use to search and query billions of relationships in milliseconds across thousands of concurrent queries.
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Neptune Analytics Learn more about Neptune Analytics - an analytics database engine that supports graph analytics, graph algorithms, and vector search of graph data.
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Neptune Graph Data Model Learn more about the Neptune Graph Data Model and how to structure your graph data effectively.
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Migrating to Neptune Learn more about migrating your existing graph databases and applications to Amazon Neptune.
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Which one should I use – Neptune Database or Neptune Analytics Learn more about choosing between Neptune Database and Neptune Analytics based on your use case.
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Graph Algorithms Learn more about the various graph algorithms available in Neptune Analytics for path finding, community detection, centrality, and similarity analysis.
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Combining Vector Similarity Search and Graphs for GenAI applications Learn more about using vector search capabilities with graph data for generative AI applications.
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Amazon Neptune Snackables Short 15-minute videos on various topics like Neptune Serverless, Knowledge graphs, security graphs, graph algorithms, vector search and more! Watch playlist
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#GraphThat Video Series The #GraphThat series features Amazon Neptune specialists taking public datasets and converting them to a graph model optimized for Amazon Neptune. Watch playlist
- AWS re:Invent 2024 - Deep dive into Amazon Neptune and its innovations (DAT317)
- AWS re:Invent 2024 - Generative AI–powered graph for network digital twin (TLC202)
- AWS re:Invent 2023 - Amazon Neptune architectures for scale, availability, and insight (DAT406)
- AWS re:Invent 2023 - Deep dive into Amazon Neptune Analytics & its generative AI capabilities (DAT325)
- AWS re:Invent 2023 - Amazon Neptune Analytics: New capabilities for graph analytics & gen AI (DAT208)
- How to perform GraphRAG with Amazon Neptune | The Data Dive on AWS OnAir S01
- Amazon Neptune: Simplifying Graph Queries With LLMs and LangChain
- Security graphs with Amazon Neptune
- Network Genius: Transforming Operations with Graph ML and generative AI
Getting Started with Amazon Neptune - 7 videos, approximately 9 hours of content
Build Your First Graph Application with Amazon Neptune - Hands-on workshop experience
- Amazon Neptune Service Introduction (5 minutes)
- Amazon Neptune Learning Plan (5 hours, 30 minutes)
We have published AWS Reference Architectures using Amazon Neptune to help inform your choices about graph data models and query languages as well as providing reference deployment architectures.
- Amazon Neptune Open Source Assets - README contains links to Amazon Neptune GitHub assets including managed libraries, examples, and utilities.
- Amazon Neptune Tools and Utilities - Data Conversion, Bulk Export, AWS Glue integration
- Amazon Neptune GraphRAG Toolkit - open source library for building GraphRAG applications using Neptune
- Amazon Neptune LangChain integration for SPARQL - SPARQL support for LangChain
- Amazon Neptune LangChain integration for openCypher - openCypher support for LangChain
- Amazon Neptune LlamaIndex integration - Llamaindex support for Neptune
- AWS Graph Notebook - Jupyter notebooks for graph exploration and development
- AWS Graph Explorer - Visual graph exploration tool
"A graph database gives us more flexibility than the relational systems. We might need to do a lot of joins on our tables [in a relational model], and that would have caused high latency of a lot of our business logic. A graph database is optimized for our use case. Amazon Neptune solved what we were trying to solve."
Mayank Gupta, Software Engineer - Audible for Business
metaphactory and Amazon Neptune enabled Siemens Energy to build a Turbine Knowledge Graph and visualize the connections between similar parts across the entire fleet of gas turbines. Amazon Neptune fits perfectly into the cloud-first strategy driven by Siemens Energy IT.
"We chose Neptune because it is a powerful graph database that is secure, performant, and analytics-friendly. In our [contact tracing] model, each user node is connected to a device node. Neptune allows us to store these rich relationships between users, check-ins, and locations to derive insight about the spread of the virus."
Aron Szanto, Co-Founder - Zerobase
"We like app-level encryption in addition to database-level encryption. When we use Amazon Neptune, the data is already encrypted before it gets to the database, and then it's encrypted again at rest."
Zaid Masud, Chief Architect, ADP's next gen HCM
"By leveraging [Amazon] Neptune and other AWS services, we are able to achieve a cost-efficient data platform, at scale, in a very short period of time."
Sasikala Singamaneni, Software Engineering Manager - Zeta Global
- Accenture: Natural Language Processing and Graph Databases for the Oil and Gas Industry (6:23)
- Nike: A Social Graph at Scale with Amazon Neptune (7:00)
- AWS re:Invent 2020: Building the post-cookie identity graph for marketing (30:48)
- AWS re:Invent 2020: ADP's next-generation platform powers dynamic teams with Amazon Neptune (26:02)
- AWS re:Invent 2019: Real-world customer use cases with Amazon Neptune (30:25)
- AWS re:Invent 2018: Building a Social Graph at Nike with Amazon Neptune (53:46)
- AWS re:Invent 2018: Data & Analysis with Amazon Neptune: A Study in Healthcare Billing (48:49)
- AWS re:Invent 2017: Amazon Neptune Overview and Customer Use Cases (1:00:56)
- AWS re:Invent 2022 - Deep dive into Amazon Neptune Serverless (53:04)
- AWS Summit SF 2022 - Amazon Neptune: Using graphs to gain security insights (56:43)
- AWS re:Invent 2021 - Real-world use cases with graph databases (31:25)
- AWS re:Invent 2020: Deep dive on Amazon Neptune (29:50)
- AWS re:Invent 2020: New capabilities to build graph apps quickly with Amazon Neptune (26:54)
- AWS on Air 2020: AWS What's Next ft. Amazon Neptune ML (24:05)
- Build Event Driven Graph Applications with AWS Purpose-Built Databases (48:03)
- Understanding Game Changes and Player Behavior with Graph Databases (50:21)
- AWS DMS supports copying data from relational databases to Amazon Neptune (1:02:34)
- Amazon Neptune: Build Applications for Highly Connected Datasets (32:33)
- AWS Tel Aviv Summit 2018: How Amazon Neptune and Graph Databases Can Transform Your Business (38:39)
- AWS re:Invent 2018: How Do I Know I Need an Amazon Neptune Graph Database? (46:12)
See all Amazon Neptune posts on the AWS Database Blog
Learn more about Amazon Neptune features and capabilities.
Get started building with Amazon Neptune on the AWS Management Console.